While nearly all epidemiologic studies involve a certain level of bias, the unique characteristics of the WTC responder cohort (NY/NJ WTC Consortium) have raised concerns regarding the potential impacts of bias in its use for epidemiologic research. The cohort was established shortly after 9/11 (April 2002) to provide health screenings for WTC responders and to create a rapid medical surveillance system. At that time, there were no clear procedural guidelines for how to quickly implement a medical screening system where data are collected in a manner that can later be used for research. Since then, numerous problems have arisen as researchers attempt to utilize this cohort data for epidemiologic research. These problems include: multiple revisions of questionnaires during follow-up health monitoring visits, poor data reliability (missing and unmatched data across follow-ups), low retention rate for follow-up visits (loss to follow-up), and significantly differet rates of referral to treatment from the health monitoring program across the five clinical centers, among others. The previous examples may be fundamental sources of bias. Often WTC health studies discuss some potential biases to explain their findings, such as the healthy worker effect, self-selection bias, and recall bias. However, none of these studies have provided evidence of the presence of bias, and none have quantified the effect of bias on causal inference. The main goal of the proposed study is to assess the impacts of epidemiologic biases in WTC health studies by identifying the presence of bias and then by quantifying and adjusting for the bias effects. To achieve this goal, we will evaluate the impacts of biases on four differen health outcomes with different latencies and severities: sinusitis, asthma, sarcoidosis, and post-traumatic stress disorder. Each of these health outcomes have shown elevated rates among WTC responders, though the associations with WTC exposure were relatively weak. We hypothesize that by identifying and adjusting for bias, the accuracy of WTC health studies can be improved, potentially strengthening associations with health outcomes like the four we propose to study. In this study, bias effects will be evaluated using two approaches: internal-validation data for direct quantification of bias effects and the utilization of published methods or quantifying bias effects when no validation data are available. While the true magnitude of a bias cannot be established with certainty, plausible ranges can be determined and used to generate bias-adjusted estimates of the effects. These bias-adjusted effect estimates are more likely to reflect true health effects. The successful completion of the proposed bias analysis will assist other researchers in drawing plausible inferences on WTC health effects by providing recommendations to identify the presence of, and adjust for bias. In addition, the study will recommend guidelines for future disaster studies which may minimize various sources of bias from the study design through data interpretation.